class_docstr: This enumeration represents optional conversion options.
  
  These conversion options are experimental. They are subject to change without
  notice and offer no guarantees.
  
  _Example Usage_
  
  ```python
  optionals= tf.autograph.experimental.Feature.EQUALITY_OPERATORS
  @tf.function(experimental_autograph_options=optionals)
  def f(i):
    if i == 0:  # EQUALITY_OPERATORS allows the use of == here.
      tf.print('i is zero')
  ```
  
  Attributes:
    ALL: Enable all features.
    AUTO_CONTROL_DEPS: Insert of control dependencies in the generated code.
    ASSERT_STATEMENTS: Convert Tensor-dependent assert statements to tf.Assert.
    BUILTIN_FUNCTIONS: Convert builtin functions applied to Tensors to
      their TF counterparts.
    EQUALITY_OPERATORS: Whether to convert the equality operator ('==') to
      tf.math.equal.
    LISTS: Convert list idioms, like initializers, slices, append, etc.
    NAME_SCOPES: Insert name scopes that name ops according to context, like the
      function they were defined in.
docstr: Returns a tuple that enables all but the excluded options.
docstr_tok: ["Returns","a","tuple","that","enables","all","but","the","excluded","options","."]
code: def all_but(cls, exclude):
      """Returns a tuple that enables all but the excluded options."""
      if not isinstance(exclude, (list, tuple, set)):
          exclude = (exclude,)
      return tuple(set(cls.all()) - set(exclude) - {cls.ALL})
  
imports: import enum
  from tensorflow.python.autograph.pyct import anno
  from tensorflow.python.autograph.pyct import ast_util
  from tensorflow.python.autograph.pyct import parser
  from tensorflow.python.autograph.pyct import templates
  from tensorflow.python.autograph.pyct import transformer
  from tensorflow.python.util.tf_export import tf_export
label_desc: Use image node_id 2 for calling the Feature obj's underlying member method code with example usage: obj.all_but(cls, exclude) and returns: tuple